metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
datasets:
- generator
metrics:
- accuracy
- f1
model-index:
- name: stool-condition-classification
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: stool-image
type: generator
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.941747572815534
- name: F1
type: f1
value: 0.9285714285714285
pipeline_tag: image-classification
stool-condition-classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the stool-image dataset. It achieves the following results on the evaluation set:
- Loss: 0.4076
- Auroc: 0.9357
- Accuracy: 0.9417
- Sensitivity: 0.8864
- Specificty: 0.9831
- F1: 0.9286
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Auroc | Accuracy | Sensitivity | Specificty | F1 |
|---|---|---|---|---|---|---|---|---|
| 0.4127 | 0.98 | 100 | 0.4406 | 0.8789 | 0.8100 | 0.7472 | 0.8657 | 0.7870 |
| 0.3473 | 1.96 | 200 | 0.4249 | 0.8774 | 0.8074 | 0.7247 | 0.8806 | 0.7795 |
Framework versions
- Transformers 4.36.1
- Pytorch 2.0.1
- Datasets 2.15.0
- Tokenizers 0.15.0